Posbist fault tree analysis of coherent systems

Huang, Hong‐Zhong; Tong, Xin; Zuo, Ming J.

doi:10.1016/j.ress.2003.11.002

Cited by 139 publications

(95 citation statements)

References 20 publications

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“…Many theoretical advances and practical applications have been achieved in this field to date. FTA is based on Boolean algebra and probability theory and it is consistent with the conventional reliability theory [7].…”

Section: Human Reliability Analysismentioning

confidence: 99%

Evaluation of the causes of Bukit Antarabangsa 2008 landslide by using fault tree analysis

Kazmi¹,

Qasim²,

Harahap³

2017

MATEC Web Conf.

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Abstract. Bukit Antarabangsa 2008 is considered as a deep-seated landslide which occurred in the landslide-prone area of Ulu Klang, Malaysia. The precipitation data obtained from previous studies show that there were comparatively less rainfalls immediately before the landslide which suggests that other potential triggers must be analyzed. This study analyses the causes of Bukit Antarabangsa 2008 landslide by performing fault tree analysis (FTA) which is a logical and diagrammatic method to evaluate the probability of an accident resulting from sequences and combinations of faults. The FTA is performed on four potential landslide contributors of improper shear strength parameters, flawed development plan, erroneous drainage planning & design and, ineffective slope strengthening works in order to determine the causes of the landslide. The analysis shows that the causes of Bukit Antarabangsa 2008 landslide potentially include ineffective slope strengthening works related to monitoring and maintenance which is followed by improper development plan having a probability of failure of 0.194 and 0.15 respectively. These causes actually correlate with the human errors which are often neglected during the slope construction and required to be addressed to increase the safety of the slopes.

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Section: Human Reliability Analysismentioning

confidence: 99%

Evaluation of the causes of Bukit Antarabangsa 2008 landslide by using fault tree analysis

Kazmi¹,

Qasim²,

Harahap³

2017

MATEC Web Conf.

View full text Add to dashboard Cite

show abstract

“…In different phases of modeling and simulation, uncertainty arises from the following (Robinson, 1998;Agarwal et al, 2004;Huang et al, 2004;2006c;2012b):…”

Section: Sources Of Uncertaintymentioning

confidence: 99%

“…Modeling of reliability using a new data fusion rule is proposed by Delmotte and Borne (1998); Sun et al (2008) and Yang et al (2011a); Possibility-based design optimization is studied and developed by (Mourelatos and Zhou, 2004;Youn, 2005;Youn and Choi, 2004a;Youn et al, 2004;Choi et al, 2004;2012b;Zhang et al, 2010b). Fuzzy reliability theory in the context of possibility theory is proposed and developed by (Cai et al, 1991a;1991b;1993;Utkin and Gurov, 1996;Onisawa, 1988;Huang et al, 2004;. In addition to reliability engineering, the application areas also include civil engineering and structural engineering (Moller et al, 1999;Huang et al, 2011a;Huang, 2012), computational mechanics, military, energy, forestry (Kangas and Kangas, 2004), aerospace and automobile engineering (Cayrac et al, 1996) and many other fields.…”

Section: General Topics Of Applicationsmentioning

confidence: 99%

“…One is theoretic development related to the fundamentals of reliability theory, e.g. imprecise reliability (Walley, 1991;Utkin and Coolen, 2007;Kozine and Filimonov, 2000) and fuzzy reliability (Cai et al, 1991a;1991b;1993;Huang et al, 2004;; the other is computational (or algorithmic) development in analysis and the design method, e.g., data fusion technology applied to reliability assessment (Hall and Llinas, 1997;Zhang et al, 2010a;Sun et al, 2008;Yang, 2011a; and optimum design methods (Youn and Choi, 2004b;Youn et al, 2004;Aughenbaugh and Paredis, 2005;Huang et al, 2005a;Limbourg, 2005;Mourelatos and Zhou, 2005;Huang et al, 2006a;2012a). These are illustrated in the sections that follow.…”

Section: General Topics Of Applicationsmentioning

confidence: 99%

“…• Lack of information in input data, small sample size, insufficient information or scarce data (Chen et al, 1999;Mourelatos and Zhou, 2004;Nikolaidis and Haftka, 2001;Huang et al, 2004; • Imprecise data or lack of knowledge Youn and Choi, 2004a;Youn et al, 2004;Aughenbaugh and Paredis, 2005;Huang et al, 2005b;2006d;Limbourg, 2005;Mourelatos and Zhou, 2005) • Large-scale, complex or costly systems (Zhuang et al, 2000) …”

Section: Ajeasmentioning

confidence: 99%

See 2 more Smart Citations

Possibility and Evidence-Based Reliability Analysis and Design Optimization

Huang

Liu

et al. 2013

American Journal of Engineering and Applied Sciences

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Engineering design under uncertainty has gained considerable attention in recent years. A great multitude of new design optimization methodologies and reliability analysis approaches are put forth with the aim of accommodating various uncertainties. Uncertainties in practical engineering applications are commonly classified into two categories, i.e., aleatory uncertainty and epistemic uncertainty. Aleatory uncertainty arises because of unpredictable variation in the performance and processes of systems, it is irreducible even adding more data or knowledge. On the other hand, epistemic uncertainty stems from lack of knowledge of the system due to limited data, measurement limitations, or simplified approximations in modeling system behavior and it can be reduced by obtaining more data or knowledge. More specifically, aleatory uncertainty is naturally represented by a statistical distribution and its associated parameters can be characterized by sufficient data. If, however, the data is limited and can be quantified in a statistical sense, epistemic uncertainty can be considered as an alternative tool in such a situation. Of the several optional treatments for epistemic uncertainty, possibility theory and evidence theory have proved to be the most computationally efficient and stable for reliability analysis and engineering design optimization. This study first attempts to provide a better understanding of uncertainty in engineering design by giving a comprehensive overview of its classifications, theories and design considerations. Then a review is conducted of general topics such as the foundations and applications of possibility theory and evidence theory. This overview includes the most recent results from theoretical research, computational developments and performance improvement of possibility theory and evidence theory with an emphasis on revealing the capability and characteristics of quantifying uncertainty from different perspectives. Possibility and evidence theory-based reliability methods have many advantages for practical engineering when compared with traditional probability-based reliability methods. They can work well under limited data while the latter need large amounts of information, more than possible in engineering practice due to aleatory and epistemic uncertainties. The possible directions for future work are summarized.

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Risk Assessment of Railway Transportation Systems using Timed Fault Trees

Peng

Miller

et al. 2014

Qual. Reliab. Engng. Int.

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aSafety is an essential requirement for railway transportation. There are many methods that have been developed to predict, prevent, and mitigate accidents in this context. All of these methods have their own purpose and limitations. This paper presents a new useful analysis technique: timed fault tree analysis. This method extends traditional fault tree analysis with temporal events and fault characteristics. Timed fault trees (TFTs) can determine which faults need to be eliminated urgently, and it can also provide how much time have been left at least to eliminate the root failure to prevent accidents. They can also be used to determine the time taken for railway maintenance requirements, and thereby improve maintenance efficiency, and reduce risks. In this paper, we present the features and functionality of a railway transportation system, and principles and rules of TFTs. We demonstrate the applicability of our framework by a case study on a simple railway transportation system.

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Posbist fault tree analysis of coherent systems

Cited by 139 publications

References 20 publications

Evaluation of the causes of Bukit Antarabangsa 2008 landslide by using fault tree analysis

Evaluation of the causes of Bukit Antarabangsa 2008 landslide by using fault tree analysis

Possibility and Evidence-Based Reliability Analysis and Design Optimization

Risk Assessment of Railway Transportation Systems using Timed Fault Trees

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